文献类型：期刊文献

英文题名：Kinetic Model-Constrained Robust In-Motion Alignment for Projectiles SINS/GNSS

作者：Gao, Ning Chen, Xiyuan Yan, Zhe

第一作者：Gao, Ning

通信作者：Chen, XY[1];Chen, XY[2]

机构：[1]Southeast Univ, State Key Lab Comprehens PNTNetwork & Equipment Te, Sch Instrument Sci & Engn, Minist Educ, Nanjing 210018, Peoples R China;[2]Southeast Univ, Key Lab Microinertial Instrument & Adv Nav Technol, Minist Educ, Nanjing 210018, Peoples R China;[3]Guizhou Inst Technol, Sch Aerosp Engn, Guiyang 550025, Peoples R China

第一机构：Southeast Univ, State Key Lab Comprehens PNTNetwork & Equipment Te, Sch Instrument Sci & Engn, Minist Educ, Nanjing 210018, Peoples R China

通信机构：corresponding author), Southeast Univ, State Key Lab Comprehens PNTNetwork & Equipment Te, Sch Instrument Sci & Engn, Minist Educ, Nanjing 210018, Peoples R China;corresponding author), Southeast Univ, Key Lab Microinertial Instrument & Adv Nav Technol, Minist Educ, Nanjing 210018, Peoples R China.

年份：2025

卷号：25

期号：20

起止页码：38847-38856

外文期刊名：IEEE SENSORS JOURNAL

收录：;EI(收录号：20253919212721);Scopus(收录号：2-s2.0-105016584890);WOS:【SCI-EXPANDED(收录号:WOS:001594911000045)】；

基金：This work was supported in part by the National Natural Science Foundation of China under Grant 61873064 and Grant 42404026; and in part by the Foundation of Key Laboratory of Micro-Inertial Instrument and Advanced Navigation Technology, Ministry of Education, China.

语种：英文

外文关键词：Global navigation satellite system; Vectors; Accuracy; Projectiles; Robustness; Inertial navigation; Convergence; Gyroscopes; Force; Estimation; Extended Kalman filter (EKF); guided projectiles; initial alignment; model constraints; optimization-based in-motion alignment (OBIA); vector construction

摘要：Rapid and accurate initial alignment is a critical prerequisite for the performance in integrated navigation of strapdown inertial navigation system (SINS) and global navigation satellite system (GNSS), particularly in guided projectiles operating under in-motion conditions. However, conventional optimization-based in-motion alignment (OBIA) methods often suffer from slow convergence and reduced accuracy in the presence of degraded GNSS signals and the cumulative errors of low-cost microelectromechanical system (MEMS)-based inertial measurement unit (IMU). To address these challenges, this article introduces a novel kinetic model-constrained robust in-motion alignment approach tailored for projectile applications. The proposed method integrates a simplified ballistic trajectory model into an extended Kalman filter (EKF) to constrain GNSS measurements, while innovation-based anomaly detection and an adaptive filtering strategy enhance robustness against GNSS outliers. Furthermore, a sliding-window integration scheme is employed to suppress drift errors from the MEMS-based IMU. Semi-physical simulation experiments under both nominal and degraded GNSS conditions demonstrate that the proposed method significantly outperforms conventional OBIA techniques in terms of convergence speed, alignment accuracy, and resistance to interference. These findings validate the proposed approach as an effective solution for rapid and robust initial alignment in time-critical projectile navigation scenarios.